mirror of
https://github.com/qurator-spk/eynollah.git
synced 2025-06-09 20:29:55 +02:00
rename: image_{dir,filename}, {f_name,image_filename_stem}
This commit is contained in:
Konstantin Baierer
parent
f5e11a1056
commit
52df6972ad
2 changed files with 10 additions and 123 deletions
|
|
@ -1,3 +1,4 @@
|
|||
# pylint: disable=no-member
|
||||
"""
|
||||
tool to extract table form data from alto xml data
|
||||
"""
|
||||
|
|
@ -200,15 +201,8 @@ class eynollah:
|
|||
nxf = img_w / float(width_mid)
|
||||
nyf = img_h / float(height_mid)
|
||||
|
||||
if nxf > int(nxf):
|
||||
nxf = int(nxf) + 1
|
||||
else:
|
||||
nxf = int(nxf)
|
||||
|
||||
if nyf > int(nyf):
|
||||
nyf = int(nyf) + 1
|
||||
else:
|
||||
nyf = int(nyf)
|
||||
nxf = int(nxf) + 1 if nxf > int(nxf) else int(nxf)
|
||||
nyf = int(nyf) + 1 if nyf > int(nyf) else int(nyf)
|
||||
|
||||
for i in range(nxf):
|
||||
for j in range(nyf):
|
||||
|
|
@ -295,7 +289,6 @@ class eynollah:
|
|||
return int(float(dpi))
|
||||
|
||||
def resize_image_with_column_classifier(self, is_image_enhanced):
|
||||
dpi = self.check_dpi()
|
||||
img = cv2.imread(self.image_filename)
|
||||
img = img.astype(np.uint8)
|
||||
|
||||
|
|
@ -540,11 +533,6 @@ class eynollah:
|
|||
image_res = self.predict_enhancement(img_new)
|
||||
# cv2.imwrite(os.path.join(self.dir_out, self.image_filename_stem) + ".tif",self.image)
|
||||
# self.image=self.image.astype(np.uint16)
|
||||
|
||||
# self.scale_x=1
|
||||
# self.scale_y=1
|
||||
# self.height_org = self.image.shape[0]
|
||||
# self.width_org = self.image.shape[1]
|
||||
is_image_enhanced = True
|
||||
else:
|
||||
is_image_enhanced = False
|
||||
|
|
@ -570,8 +558,6 @@ class eynollah:
|
|||
|
||||
def get_image_and_scales_after_enhancing(self, img_org, img_res):
|
||||
|
||||
# self.image = cv2.imread(self.image_filename)
|
||||
|
||||
self.image = np.copy(img_res)
|
||||
self.image = self.image.astype(np.uint8)
|
||||
self.image_org = np.copy(img_org)
|
||||
|
|
@ -630,15 +616,8 @@ class eynollah:
|
|||
nxf = img_w / float(width_mid)
|
||||
nyf = img_h / float(height_mid)
|
||||
|
||||
if nxf > int(nxf):
|
||||
nxf = int(nxf) + 1
|
||||
else:
|
||||
nxf = int(nxf)
|
||||
|
||||
if nyf > int(nyf):
|
||||
nyf = int(nyf) + 1
|
||||
else:
|
||||
nyf = int(nyf)
|
||||
nxf = int(nxf) + 1 if nxf > int(nxf) else int(nxf)
|
||||
nyf = int(nyf) + 1 if nyf > int(nyf) else int(nyf)
|
||||
|
||||
for i in range(nxf):
|
||||
for j in range(nyf):
|
||||
|
|
@ -665,11 +644,8 @@ class eynollah:
|
|||
index_y_d = img_h - img_height_model
|
||||
|
||||
img_patch = img[index_y_d:index_y_u, index_x_d:index_x_u, :]
|
||||
|
||||
label_p_pred = model.predict(img_patch.reshape(1, img_patch.shape[0], img_patch.shape[1], img_patch.shape[2]))
|
||||
|
||||
seg = np.argmax(label_p_pred, axis=3)[0]
|
||||
|
||||
seg_color = np.repeat(seg[:, :, np.newaxis], 3, axis=2)
|
||||
|
||||
if i == 0 and j == 0:
|
||||
|
|
|
|||
|
|
@ -1485,7 +1485,7 @@ def textline_contours_postprocessing(textline_mask, slope, contour_text_interest
|
|||
|
||||
return contours_rotated_clean
|
||||
|
||||
def seperate_lines_new2(img_path, thetha, num_col, slope_region, dir_of_all, f_name):
|
||||
def seperate_lines_new2(img_path, thetha, num_col, slope_region, dir_of_all, image_filename_stem):
|
||||
|
||||
if num_col == 1:
|
||||
num_patches = int(img_path.shape[1] / 200.0)
|
||||
|
|
@ -1536,7 +1536,7 @@ def seperate_lines_new2(img_path, thetha, num_col, slope_region, dir_of_all, f_n
|
|||
|
||||
sigma = 2
|
||||
try:
|
||||
slope_xline = return_deskew_slop(img_xline, sigma, dir_of_all=dir_of_all, f_name=f_name)
|
||||
slope_xline = return_deskew_slop(img_xline, sigma, dir_of_all=dir_of_all, image_filename_stem=image_filename_stem)
|
||||
except:
|
||||
slope_xline = 0
|
||||
|
||||
|
|
@ -1593,7 +1593,7 @@ def seperate_lines_new2(img_path, thetha, num_col, slope_region, dir_of_all, f_n
|
|||
# plt.show()
|
||||
return img_patch_ineterst_revised
|
||||
|
||||
def return_deskew_slop(img_patch_org, sigma_des, main_page=False, dir_of_all=None, f_name=None):
|
||||
def return_deskew_slop(img_patch_org, sigma_des, main_page=False, dir_of_all=None, image_filename_stem=None):
|
||||
|
||||
|
||||
if main_page and dir_of_all is not None:
|
||||
|
|
@ -1610,7 +1610,7 @@ def return_deskew_slop(img_patch_org, sigma_des, main_page=False, dir_of_all=Non
|
|||
plt.yticks([0,len(gaussian_filter1d(img_patch_org.sum(axis=1), 3))])
|
||||
plt.gca().invert_yaxis()
|
||||
|
||||
plt.savefig(os.path.join(dir_of_all, f_name+'_density_of_textline.png'))
|
||||
plt.savefig(os.path.join(dir_of_all, image_filename_stem+'_density_of_textline.png'))
|
||||
#print(np.max(img_patch_org.sum(axis=0)) ,np.max(img_patch_org.sum(axis=1)),'axislar')
|
||||
|
||||
#img_patch_org=resize_image(img_patch_org,int(img_patch_org.shape[0]*2.5),int(img_patch_org.shape[1]/2.5))
|
||||
|
|
@ -1647,53 +1647,23 @@ def return_deskew_slop(img_patch_org, sigma_des, main_page=False, dir_of_all=Non
|
|||
#plt.show()
|
||||
angels=np.array([-45, 0 , 45 , 90 , ])#np.linspace(-12,12,100)#np.array([0 , 45 , 90 , -45])
|
||||
|
||||
#res=[]
|
||||
#num_of_peaks=[]
|
||||
#index_cor=[]
|
||||
var_res=[]
|
||||
|
||||
#indexer=0
|
||||
for rot in angels:
|
||||
img_rot=rotate_image(img_resized,rot)
|
||||
#plt.imshow(img_rot)
|
||||
#plt.show()
|
||||
img_rot[img_rot!=0]=1
|
||||
#res_me=np.mean(self.find_num_col_deskew(img_rot,sigma_des,2.0 ))
|
||||
|
||||
|
||||
#neg_peaks,var_spectrum=self.find_num_col_deskew(img_rot,sigma_des,20.3 )
|
||||
#print(var_spectrum,'var_spectrum')
|
||||
try:
|
||||
var_spectrum=find_num_col_deskew(img_rot,sigma_des,20.3 )
|
||||
##print(rot,var_spectrum,'var_spectrum')
|
||||
#res_me=np.mean(neg_peaks)
|
||||
#if res_me==0:
|
||||
#res_me=1000000000000000000000
|
||||
#else:
|
||||
#pass
|
||||
|
||||
#res_num=len(neg_peaks)
|
||||
except:
|
||||
#res_me=1000000000000000000000
|
||||
#res_num=0
|
||||
var_spectrum=0
|
||||
#if self.isNaN(res_me):
|
||||
#pass
|
||||
#else:
|
||||
#res.append( res_me )
|
||||
#var_res.append(var_spectrum)
|
||||
#num_of_peaks.append( res_num )
|
||||
#index_cor.append(indexer)
|
||||
#indexer=indexer+1
|
||||
|
||||
var_res.append(var_spectrum)
|
||||
#index_cor.append(indexer)
|
||||
#indexer=indexer+1
|
||||
|
||||
|
||||
try:
|
||||
var_res=np.array(var_res)
|
||||
|
||||
ang_int=angels[np.argmax(var_res)]#angels_sorted[arg_final]#angels[arg_sort_early[arg_sort[arg_final]]]#angels[arg_fin]
|
||||
except:
|
||||
ang_int=0
|
||||
|
|
@ -1701,32 +1671,19 @@ def return_deskew_slop(img_patch_org, sigma_des, main_page=False, dir_of_all=Non
|
|||
|
||||
angels=np.linspace(ang_int-22.5,ang_int+22.5,100)
|
||||
|
||||
#res=[]
|
||||
#num_of_peaks=[]
|
||||
#index_cor=[]
|
||||
var_res=[]
|
||||
|
||||
|
||||
for rot in angels:
|
||||
img_rot=rotate_image(img_resized,rot)
|
||||
##plt.imshow(img_rot)
|
||||
##plt.show()
|
||||
img_rot[img_rot!=0]=1
|
||||
#res_me=np.mean(self.find_num_col_deskew(img_rot,sigma_des,2.0 ))
|
||||
try:
|
||||
var_spectrum=find_num_col_deskew(img_rot,sigma_des,20.3 )
|
||||
|
||||
except:
|
||||
var_spectrum=0
|
||||
|
||||
var_res.append(var_spectrum)
|
||||
|
||||
|
||||
|
||||
|
||||
try:
|
||||
var_res=np.array(var_res)
|
||||
|
||||
ang_int=angels[np.argmax(var_res)]#angels_sorted[arg_final]#angels[arg_sort_early[arg_sort[arg_final]]]#angels[arg_fin]
|
||||
except:
|
||||
ang_int=0
|
||||
|
|
@ -1745,9 +1702,6 @@ def return_deskew_slop(img_patch_org, sigma_des, main_page=False, dir_of_all=Non
|
|||
#plt.imshow(img_rot)
|
||||
#plt.show()
|
||||
img_rot[img_rot!=0]=1
|
||||
#res_me=np.mean(self.find_num_col_deskew(img_rot,sigma_des,2.0 ))
|
||||
|
||||
|
||||
#neg_peaks,var_spectrum=self.find_num_col_deskew(img_rot,sigma_des,20.3 )
|
||||
#print(var_spectrum,'var_spectrum')
|
||||
try:
|
||||
|
|
@ -1769,41 +1723,29 @@ def return_deskew_slop(img_patch_org, sigma_des, main_page=False, dir_of_all=Non
|
|||
|
||||
plt.plot(angels[np.argmax(var_res)],var_res[np.argmax(np.array(var_res))] ,'*',markersize=50,label='Angle of deskewing=' +str("{:.2f}".format(angels[np.argmax(var_res)]))+r'$\degree$')
|
||||
plt.legend(loc='best')
|
||||
plt.savefig(os.path.join(dir_of_all,f_name+'_rotation_angle.png'))
|
||||
|
||||
|
||||
plt.savefig(os.path.join(dir_of_all,image_filename_stem+'_rotation_angle.png'))
|
||||
try:
|
||||
var_res=np.array(var_res)
|
||||
|
||||
ang_int=angels[np.argmax(var_res)]#angels_sorted[arg_final]#angels[arg_sort_early[arg_sort[arg_final]]]#angels[arg_fin]
|
||||
except:
|
||||
ang_int=0
|
||||
|
||||
|
||||
early_slope_edge=11
|
||||
if abs(ang_int)>early_slope_edge and ang_int<0:
|
||||
|
||||
angels=np.linspace(-90,-12,100)
|
||||
|
||||
var_res=[]
|
||||
|
||||
for rot in angels:
|
||||
img_rot=rotate_image(img_resized,rot)
|
||||
##plt.imshow(img_rot)
|
||||
##plt.show()
|
||||
img_rot[img_rot!=0]=1
|
||||
#res_me=np.mean(self.find_num_col_deskew(img_rot,sigma_des,2.0 ))
|
||||
try:
|
||||
var_spectrum=find_num_col_deskew(img_rot,sigma_des,20.3 )
|
||||
except:
|
||||
var_spectrum=0
|
||||
|
||||
var_res.append(var_spectrum)
|
||||
|
||||
|
||||
try:
|
||||
var_res=np.array(var_res)
|
||||
|
||||
ang_int=angels[np.argmax(var_res)]#angels_sorted[arg_final]#angels[arg_sort_early[arg_sort[arg_final]]]#angels[arg_fin]
|
||||
except:
|
||||
ang_int=0
|
||||
|
|
@ -1811,67 +1753,47 @@ def return_deskew_slop(img_patch_org, sigma_des, main_page=False, dir_of_all=Non
|
|||
elif abs(ang_int)>early_slope_edge and ang_int>0:
|
||||
|
||||
angels=np.linspace(90,12,100)
|
||||
|
||||
|
||||
var_res=[]
|
||||
|
||||
for rot in angels:
|
||||
img_rot=rotate_image(img_resized,rot)
|
||||
##plt.imshow(img_rot)
|
||||
##plt.show()
|
||||
img_rot[img_rot!=0]=1
|
||||
#res_me=np.mean(self.find_num_col_deskew(img_rot,sigma_des,2.0 ))
|
||||
try:
|
||||
var_spectrum=find_num_col_deskew(img_rot,sigma_des,20.3 )
|
||||
#print(indexer,'indexer')
|
||||
except:
|
||||
var_spectrum=0
|
||||
|
||||
var_res.append(var_spectrum)
|
||||
|
||||
|
||||
try:
|
||||
var_res=np.array(var_res)
|
||||
|
||||
ang_int=angels[np.argmax(var_res)]#angels_sorted[arg_final]#angels[arg_sort_early[arg_sort[arg_final]]]#angels[arg_fin]
|
||||
except:
|
||||
ang_int=0
|
||||
else:
|
||||
|
||||
|
||||
angels=np.linspace(-25,25,60)
|
||||
|
||||
var_res=[]
|
||||
|
||||
indexer=0
|
||||
for rot in angels:
|
||||
img_rot=rotate_image(img_resized,rot)
|
||||
#plt.imshow(img_rot)
|
||||
#plt.show()
|
||||
img_rot[img_rot!=0]=1
|
||||
#res_me=np.mean(self.find_num_col_deskew(img_rot,sigma_des,2.0 ))
|
||||
|
||||
|
||||
#neg_peaks,var_spectrum=self.find_num_col_deskew(img_rot,sigma_des,20.3 )
|
||||
#print(var_spectrum,'var_spectrum')
|
||||
try:
|
||||
var_spectrum=find_num_col_deskew(img_rot,sigma_des,20.3 )
|
||||
except:
|
||||
var_spectrum=0
|
||||
|
||||
var_res.append(var_spectrum)
|
||||
|
||||
|
||||
try:
|
||||
var_res=np.array(var_res)
|
||||
|
||||
ang_int=angels[np.argmax(var_res)]#angels_sorted[arg_final]#angels[arg_sort_early[arg_sort[arg_final]]]#angels[arg_fin]
|
||||
except:
|
||||
ang_int=0
|
||||
|
||||
#plt.plot(var_res)
|
||||
#plt.show()
|
||||
|
||||
##plt.plot(mom3_res)
|
||||
##plt.show()
|
||||
#print(ang_int,'ang_int111')
|
||||
|
|
@ -1888,20 +1810,14 @@ def return_deskew_slop(img_patch_org, sigma_des, main_page=False, dir_of_all=Non
|
|||
##plt.imshow(img_rot)
|
||||
##plt.show()
|
||||
img_rot[img_rot!=0]=1
|
||||
#res_me=np.mean(self.find_num_col_deskew(img_rot,sigma_des,2.0 ))
|
||||
try:
|
||||
var_spectrum=find_num_col_deskew(img_rot,sigma_des,20.3 )
|
||||
|
||||
except:
|
||||
var_spectrum=0
|
||||
|
||||
var_res.append(var_spectrum)
|
||||
|
||||
|
||||
|
||||
try:
|
||||
var_res=np.array(var_res)
|
||||
|
||||
ang_int=angels[np.argmax(var_res)]#angels_sorted[arg_final]#angels[arg_sort_early[arg_sort[arg_final]]]#angels[arg_fin]
|
||||
except:
|
||||
ang_int=0
|
||||
|
|
@ -1918,7 +1834,6 @@ def return_deskew_slop(img_patch_org, sigma_des, main_page=False, dir_of_all=Non
|
|||
##plt.imshow(img_rot)
|
||||
##plt.show()
|
||||
img_rot[img_rot!=0]=1
|
||||
#res_me=np.mean(self.find_num_col_deskew(img_rot,sigma_des,2.0 ))
|
||||
try:
|
||||
var_spectrum=find_num_col_deskew(img_rot,sigma_des,20.3 )
|
||||
#print(indexer,'indexer')
|
||||
|
|
@ -1926,12 +1841,8 @@ def return_deskew_slop(img_patch_org, sigma_des, main_page=False, dir_of_all=Non
|
|||
var_spectrum=0
|
||||
|
||||
var_res.append(var_spectrum)
|
||||
|
||||
|
||||
|
||||
try:
|
||||
var_res=np.array(var_res)
|
||||
|
||||
ang_int=angels[np.argmax(var_res)]#angels_sorted[arg_final]#angels[arg_sort_early[arg_sort[arg_final]]]#angels[arg_fin]
|
||||
except:
|
||||
ang_int=0
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue